Alireza Sharifi | Crop yield prediction | Best Researcher Award

Posted on by sciencefather

Assoc Prof Dr Alireza Sharifi |  Crop yield prediction |  Best Researcher Award

Dr at  Shahid Rajaee Teacher Training, Iran

Dr. Alireza Sharifi is an Associate Professor at Shahid Rajaee Teacher Training University, specializing in geosciences and remote sensing applications for Precision Agriculture. He obtained his graduate degree from the University of Tehran and has focused his research on Earth Observation Programs, particularly using satellite imagery. Dr. Sharifi has led multiple research projects funded by prestigious organizations such as the National Natural Science Foundation of China, contributing significantly to the fields of hyperspectral image classification, crop mapping, and vegetation monitoring. With numerous publications and a strong academic background, he continues to advance innovative approaches in agricultural sustainability through technology.

Profile:

📚 Academic Background:

Dr. Alireza Sharifi graduated from the University of Tehran with expertise in geosciences and remote sensing applications, focusing on Earth Observation Programs for Precision Agriculture using satellite imagery.

🔍 Research Focus:

His research spans various projects, including hyperspectral image classification, spatio-temporal analysis of forest fires, and integration of satellite images for crop mapping. He has published extensively in reputed journals and holds multiple editorial appointments.

📊 Citations:

  • Citations: 1970 (1878 since 2019)
  • h-index: 28 (since 2019)
  • i10-index: 40 (since 2019)
📄 Publication:

1. Comparison the accuracies of different spectral indices for estimation of vegetation cover fraction in sparse vegetated areas
S Barati, B Rayegani, M Saati, A Sharifi, M Nasri
The Egyptian Journal of Remote Sensing and Space Science 14 (1), 49-56, 2011
Citations: 221

2. Hyperspectral image classification using a hybrid 3D-2D convolutional neural networks
S Ghaderizadeh, D Abbasi-Moghadam, A Sharifi, N Zhao, A Tariq
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Citations: 132

3. Yield prediction with machine learning algorithms and satellite images
A Sharifi
Journal of the Science of Food and Agriculture 101 (3), 891-896, 2021
Citations: 105

4. Spatio-temporal analysis of forest fire events in the Margalla Hills, Islamabad, Pakistan using socio-economic and environmental variable data with machine learning methods
A Tariq, H Shu, S Siddiqui, I Munir, A Sharifi, Q Li, L Lu
Journal of Forestry Research 33 (1), 183-194, 2022
Citations: 76

5. Crop type classification by DESIS hyperspectral imagery and machine learning algorithms
N Farmonov, K Amankulova, J Szatmári, A Sharifi, D Abbasi-Moghadam, …
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Citations: 62

6. Assessing spatio-temporal mapping and monitoring of climatic variability using SPEI and RF machine learning models
SS Wahla, JH Kazmi, A Sharifi, SA Shirazi, A Tariq, H Joyell Smith
Geocarto International 37 (27), 14963-14982, 2022
Citations: 62

7. Multiscale dual-branch residual spectral–spatial network with attention for hyperspectral image classification
S Ghaderizadeh, D Abbasi-Moghadam, A Sharifi, A Tariq, S Qin
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Citations: 60

8. Evaluation of vegetation indices and phenological metrics using time-series MODIS data for monitoring vegetation change in Punjab, Pakistan
P Hu, A Sharifi, MN Tahir, A Tariq, L Zhang, F Mumtaz, SHIA Shah
Water 13 (18), 2550, 2021
Citations: 59

9. Flash flood susceptibility assessment and zonation by integrating analytic hierarchy process and frequency ratio model with diverse spatial data
A Tariq, J Yan, B Ghaffar, S Qin, BG Mousa, A Sharifi, ME Huq, M Aslam
Water 14 (19), 3069, 2022
Citations: 57

10. Remote sensing satellite’s attitude control system: rapid performance sizing for passive scan imaging mode
A Kosari, A Sharifi, A Ahmadi, M Khoshsima
Aircraft Engineering and Aerospace Technology 92 (7), 1073-1083, 2020
Citations: 57

11. Flood mapping using relevance vector machine and SAR data: A case study from Aqqala, Iran
A Sharifi
Journal of the Indian Society of Remote Sensing 48 (9), 1289-1296, 2020
Citations: 55

12. Modeling and predicting land use land cover spatiotemporal changes: A case study in Chalus Watershed, Iran
S Jalayer, A Sharifi, D Abbasi-Moghadam, A Tariq, S Qin
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Citations: 54

13. Integration of Sentinel 1 and Sentinel 2 satellite images for crop mapping
S Felegari, A Sharifi, K Moravej, M Amin, A Golchin, A Muzirafuti, A Tariq, …
Applied Sciences 11 (21), 10104, 2021
Citations: 54

14. Development of a method for flood detection based on Sentinel‐1 images and classifier algorithms
A Sharifi
Water and Environment Journal 35 (3), 924-929, 2021
Citations: 54

15. Estimation of forest biomass using multivariate relevance vector regression
A Sharifi, J Amini, R Tateishi
Photogrammetric Engineering & Remote Sensing 82 (1), 41-49, 2016
Citations: 54

16. Agro climatic zoning of saffron culture in Miyaneh city by using WLC method and remote sensing data
A Zamani, A Sharifi, S Felegari, A Tariq, N Zhao
Agriculture 12 (1), 118, 2022
Citations: 50

17. Forest biomass estimation using synthetic aperture radar polarimetric features
A Sharifi, J Amini
Journal of Applied Remote Sensing 9 (1), 097695-097695, 2015
Citations: 49

18. Remotely sensed vegetation indices for crop nutrition mapping
A Sharifi
Journal of the Science of Food and Agriculture 100 (14), 5191-5196, 2020
Citations: 47

19. Using Sentinel-2 data to predict nitrogen uptake in maize crop
A Sharifi
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Citations: 47

20. Speckle reduction of PolSAR images in forest regions using fast ICA algorithm
A Sharifi, J Amini, JT Sri Sumantyo, R Tateishi
Journal of the Indian Society of Remote Sensing 43, 339-346, 2015
Citations: 47

 

Vladimír Langraf | Agroecosystems | Best Researcher Award

Posted on by sciencefather

Assoc Prof Dr Vladimír Langraf |  Agroecosystems |  Best Researcher Award

associate professor position at  Constantine the Philosopher University in Nitra,   Slovakia

Doc. RNDr. Vladimír Langraf, PhD, serves as an Associate Professor at Constantine the Philosopher University in Nitra, Slovakia. He has an extensive academic background, completing his PhD in Landscape Protection and Exploitation in 2018 and earning his associate professorship in Biology in 2024. His research primarily focuses on agroecosystems, entomology, biostatistics, and big data.

 

Profile

Academic and Professional Background 📜

  • 2024: Habilitation in Biology, Constantine the Philosopher University in Nitra
  • 2014 – 2018: PhD in Landscape Protection and Exploitation, Constantine the Philosopher University in Nitra
  • 2015 – 2016: Rigorous Degree (RNDr) in Landscape Protection and Exploitation, Constantine the Philosopher University in Nitra
  • 2012 – 2014: Master’s Degree (Mgr) in Biology, Constantine the Philosopher University in Nitra
  • 2009 – 2012: Bachelor’s Degree (Bc) in Biology, Constantine the Philosopher University in Nitra

Agroecosystems Research Focus:

doc. RNDr. Vladimír Langraf PhD, an Associate Professor at Constantine the Philosopher University in Nitra, specializes in the study of agroecosystems. His research delves into the dynamics and interactions within agricultural environments, focusing on the composition and seasonal variation of epigeic arthropods in different types of crops and their ecotones. His work aims to understand the impact of agricultural practices on biodiversity and ecosystem health, particularly through the lens of ecological management and sustainable farming practices.

Citations:

  • Citations: 117 citations by 84 documents
  • h-index: 8

📄 Publication:

  • Habitat Structure Impact on the Occurrence Preferences and Behaviour of the Endangered Species Hipparchia hermione (Lepidoptera, Nymphalidae) in Slovakia
    • Farkasová, S., Kalivoda, H., Langraf, V., Holecová, M.
    • Ekologia Bratislava, 2024, 43(1), pp. 66–75
  • Structure of Beetles (Coleoptera) in the Conditions of Agriculturally Used Land and Natural Habitat of the European Important Territory of the Dunajské luhy
    • Langraf, V., Petrovičová, K., Brygadyrenko, V.
    • Contemporary Problems of Ecology, 2024, 17(2), pp. 325–335
  • Seasonal Dynamics of Epigeic Arthropods under the Conditions of Ecological Management of the Triticum aestivum Crop
    • Langraf, V., Petrovičová, K.
    • Agriculture (Switzerland), 2024, 14(3), 482
  • Comparison of Spatial Dispersion of Epigeic Fauna Between Alluvial Forests in an Agrarian and Dunajské luhy Protected Landscape Area, Southern Slovakia
    • Langraf, V., Petrovičová, K., David, S., Brygadyrenko, V.
    • Central European Forestry Journal, 2024, 70(1), pp. 3–10
  • Ladybird (Coleoptera, Coccinellidae) Communities on Nonnative Blue Spruce in Central Europe
    • Jauschová, T., Sarvašová, L., Saniga, M., Kulfan, J., Zach, P.
    • Folia Oecologica, 2024, 51(1), pp. 18–28

 

Vladimir Verzhuk | Sustainable Crop Production | Best Researcher Award

Posted on by sciencefather

Dr Vladimir Verzhuk |  Sustainable Crop Production |  Best Researcher Award

Senior researcher at N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR) St. Petersburg, Russia

Verzhuk Vladimir Grigorevich is a Senior Researcher at the N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR) in St. Petersburg, Russia. He holds a Candidate of Biological Sciences degree and has been a pivotal figure in the field of plant cryopreservation since completing his postgraduate studies at VIR in 1976.

 

Profile:

Academic and Professional Background:

Verzhuk Vladimir Grigorevich, a Candidate of Biological Sciences, is a Senior Researcher at the Laboratory of Long-term Storage of Plant Genetic Resources of VIR. He graduated from the Crimean Agricultural Institute in 1971 and completed his postgraduate studies at VIR in 1976, focusing on photosynthesis and productivity. Since 2000, he has led the cryopreservation group, specializing in low-temperature storage of vegetative shoots, buds, and pollen of fruit crops.

Areas of Research:

Verzhuk’s research focuses on developing and improving cryopreservation methods for the genetic resources of vegetatively propagated crops at VIR.

Sustainable Crop Production Research Focus:

Verzhuk’s research emphasizes sustainable crop production through the development of cryopreservation methods for genetic resources. His work ensures the long-term viability and diversity of crop species, contributing to the sustainability of agricultural systems by preserving genetic material that can adapt to changing environmental conditions and stressors.

Publication Top Notes:

  • Conservation of the Bird Cherry (Padus Mill.) Germplasm by Cold Storage and Cryopreservation of Winter Cuttings
    • Journal: Biology
    • Date: 2023-07
    • DOI: 10.3390/biology12081071
    • Contributors: Vladimir Verzhuk, Sergey Murashev, Liubov Novikova, Stepan Kiru, Svetlana Orlova
  • Post-Cryogenic Viability of Peach (Persica vulgaris Mill.) Dormant Buds from the VIR Genetic Collection
    • Journal: Agriculture
    • Date: 2022-12
    • DOI: 10.3390/agriculture13010111
    • Contributors: Vladimir Verzhuk, Victor Eremin, Taisya Gasanova, Oksana Eremina, Liubov Novikova, Galina Filipenko, Maxim Sitnikov, Alexander Pavlov
  • Viability of Red (Ribes rubrum L.) and Black (Ribes nigrum L.) Currant Cuttings in Field Conditions after Cryopreservation in Vapors of Liquid Nitrogen
    • Journal: Agriculture
    • Date: 2020-10
    • DOI: 10.3390/agriculture10100476
    • Contributors: Vladimir Verzhuk, Alexander Pavlov, Liubov Novikova, Galina Filipenko

 

Guoqiang Dun | Agricultural Machinery | Best Researcher Award

Posted on by sciencefather

Dr Guoqiang Dun | Agricultural Machinery | Best Researcher Award

Associate professor at  Intelligent Agricultural Machinery Equipment Engineering Laboratory, Harbin Cambridge College, China

Dr. Guoqiang Dun is a distinguished researcher in the field of intelligent agricultural machinery and equipment, with a focus on intelligent precision control sowing and fertilizing equipment, plot breeding machinery, special vegetable and herb sowing machinery, and computer simulation technology. He has authored over 40 papers in academic journals and holds more than 140 patents. In 2022, he was recognized as the first author in the “Leader 5000 – China’s Top Academic Papers in Excellence Journals (F5000)” and received the first prize in the National Agriculture, Animal Husbandry and Fisheries Harvest Award for Agricultural Technology Promotion Achievement. Dr. Dun has successfully led projects totaling nearly 600,000 RMB.

Profile:

📚 Academic and Professional Background:

Dr. Guoqiang Dun is an expert in intelligent agricultural machinery and equipment, specializing in intelligent precision control sowing and fertilizing equipment, plot breeding machinery, special vegetable and herb sowing machinery, and computer simulation technology. He has published over 40 papers and holds more than 140 patents. In 2022, he was recognized as a leading author in “Leader 5000 – China’s Top Academic Papers in Excellence Journals (F5000)” and received the first prize in the National Agriculture, Animal Husbandry and Fisheries Harvest Award. He has led projects worth nearly 600,000 RMB.

🛠️ Areas of Research:

  • Intelligent agricultural machinery and equipment
  • Intelligent precision control sowing and fertilizing equipment
  • Plot breeding machinery and equipment
  • Special vegetable and herb sowing machinery
  • Computer simulation technology

🚜 Research Focus in Agricultural Machinery:

Guoqiang Dun’s research in agricultural machinery encompasses several key areas: Intelligent Precision Control Sowing and Fertilizing Equipment: Development of advanced sowing and fertilizing machinery with precision control mechanisms. Optimization of fertilizer apparatus using discrete element methods. Plot Breeding Machinery and Equipment: Design and improvement of machinery tailored for plot breeding to enhance efficiency and precision. Innovations in seed-metering wheels and specialized seed discharge devices. Special Vegetable and Herb Sowing Machinery: Creation of specialized machinery for sowing vegetables and herbs with specific requirements. Implementation of unique mechanisms to ensure precise sowing and uniform growth. Computer Simulation Technology: Utilization of computer simulations to optimize machinery design and functionality. Application of software like EDEM and SolidWorks for dynamic simulation and analysis of agricultural processes. Guoqiang Dun’s contributions have significantly advanced the field of agricultural machinery, leading to more efficient, precise, and innovative farming practices.

Citations:

  • Citations: 203
  • Documents Cited: 176
  • Total Documents: 20
  • h-index: 8 (View h-index graph)

Publication Top Notes:

  • Design and Experiment of Side-hung Seed-rowing Spoon Type Precision Seed Metering Device for Radish | 红萝卜侧面悬置排种勺式精量排种器设计与试验
  • Design and Experiment of an Electric Control Spiral-Pushing Feed Mechanism for Field Fertilizer Applicator
  • Optimization and Experiment of the Fertilizer Apparatus with Staggered Gears | 错排齿轮式排肥器优化与试验
  • Simulation Optimization and Experiment of Screw Extrusion Precision Fertilizer Ejector | 螺旋挤压式精量排肥器的仿真优化及试验
  • Optimization Design and Experiment for Precise Control Double Arc Groove Screw Fertilizer Discharger
  • Design and Trajectory Simulation Reliability Analysis of a Self-propelled Strawberry Applicator | 自走式草莓施药机设计与轨迹仿真可靠性分析
  • Optimal Design and Experiment of Corn-Overlapped Strip Fertilizer Spreader
  • Optimization Design and Experiment of Oblique Opening Spiral Precision Control Fertilizer Apparatus | 斜口螺旋精控排肥器优化设计与试验
  • Optimization Design and Experiment of Alternate Post Changing Seed Metering Device for Soybean Plot Breeding | 交替换岗式大豆小区育种排种器优化设计与试验
  • Optimal Design and Experiment of Arc-groove Double-spiral Fertilizer Discharge Device | 弧槽双螺旋式排肥器优化设计与试验

 

 

Liang He | Agronomy | Best Researcher Award

Posted on by sciencefather

Prof Liang He | Agronomy | Best Researcher Award

dean at  Xinjiang university, China

Dr. He Liang, born in December 1981, is a distinguished professor and serves as the Executive Vice Dean of the School of Computer Science and Technology, as well as the Dean of the School of Intelligence Science and Technology at Xinjiang University. He holds a Ph.D. in Artificial Intelligence and specializes in temporal sequence signal processing, knowledge graphs, and reinforcement learning.

Profile:

Educational Background:

  • Qualification: PhD
  • Specialization: Artificial Intelligence
  • Sub-Division: Knowledge Graphs, Reinforcement Learning

Professional Experience and Achievements:

Dr. He Liang serves as the Executive Vice Dean of the School of Computer Science and Technology and Dean of the School of Intelligence and Science and Technology at Xinjiang University. With a focus on temporal sequence signal processing, knowledge graphs, and reinforcement learning, he has led over 20 scientific research projects and published over 100 academic papers in prestigious journals and conferences, including Nature Communication, IEEE Trans on ASLP, and ICASSP.

He is a well-regarded reviewer for several international journals and conferences such as IEEE Audio, Speech and Language Processing, and Pattern Recognition. Dr. Liang’s contributions to research have earned him over 1000 citations in Scopus/Web of Science.

Research and Development Contributions:

Dr. Liang has made significant contributions to the study of drought stress resistance in cotton plants, exploring optimal irrigation methods to improve yield and conserve water. His research has shown a strong correlation between deficit irrigation and improved cotton yield, leading to optimized irrigation schemes that benefit local agriculture.

Agronomy Research Focus:

Dr. He Liang has directed a significant portion of his research towards addressing agronomic challenges, particularly in the context of arid regions. His work primarily focuses on optimizing agricultural practices through advanced data-driven methodologies and artificial intelligence.

Citations:

  • H-Index: 25 (Total), 24 (Since 2019)
  • i10-Index: 66 (Total), 61 (Since 2019)
  • Total Citations: 2352 (Total), 1836 (Since 2019)

 

Publication Top Notes:

  • Applications of Chemical Vapor Generation in Non-Tetrahydroborate Media to Analytical Atomic Spectrometry
    • Year: 2010
    • Citations: 202
  • Large Margin Softmax Loss for Speaker Verification
    • Year: 2019
    • Citations: 163
  • The Trans-Omics Landscape of COVID-19
    • Year: 2021
    • Citations: 88
  • Speaker Embedding Extraction with Phonetic Information
    • Year: 2018
    • Citations: 77
  • Evaluation of Tungsten Coil Electrothermal Vaporization-Ar/H2 Flame Atomic Fluorescence Spectrometry for Determination of Eight Traditional Hydride-Forming Elements and Cadmium
    • Year: 2008
    • Citations: 55
  • Dynamics and Correlation Among Viral Positivity, Seroconversion, and Disease Severity in COVID-19: A Retrospective Study
    • Year: 2021
    • Citations: 53
  • Enhance Prototypical Network with Text Descriptions for Few-Shot Relation Classification
    • Year: 2020
    • Citations: 53
  • Simultaneous Utilization of Spectral Magnitude and Phase Information to Extract Supervectors for Speaker Verification Anti-Spoofing
    • Year: 2015
    • Citations: 52